Study on Performance of 80 Watt Floating Photovoltaic Panel

Majid, Zafri Azran Abdul; Ruslan, Mohd Hafidz; Sopian, Kamaruzzaman; Othman, Masuri; Azmi, Mohd Syahriman Mohd

doi:10.15282/jmes.7.2014.14.0112

Cited by 74 publications

(31 citation statements)

References 9 publications

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“…However, as the cost of PV modules themselves have dropped a low-tilt angle system enables closer packing of modules (e.g., higher power per unit area) and can increase the solar electricity generated per unit area at an airport. In addition, for airports with surface water, floating solar PV farms [15][16][17][18][19][20][21] and even aquavoltaics [22] would enable an increased area for PV, as well as possibly reducing water surface glare.…”

Section: Resultsmentioning

confidence: 99%

“…Much of this need can be met via rooftop PV or the relatively immature building-integrated PV (BIPV) market [5][6][7][8][9][10]. The remainder will need to be met by large-area solar PV farms on either land-based solar PV farms [11][12][13][14] or even water-based floating solar PV farms [15][16][17][18][19][20][21][22]. However, as the global population increases 1.15% per year [23], attractive land and even waterways will become more valuable, especially in densely populated areas.…”

Section: Introductionmentioning

confidence: 99%

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General Design Procedures for Airport-Based Solar Photovoltaic Systems

et al. 2017

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A source of large surface areas for solar photovoltaic (PV) farms that has been largely overlooked in the 13,000 United States of America (U.S.) airports. This paper hopes to enable PV deployments in most airports by providing an approach to overcome the three primary challenges identified by the Federal Aviation Administration (FAA): (1) reflectivity and glare; (2) radar interference; and (3) physical penetration of airspace. First, these challenges and precautions that must be adhered to for safe PV projects deployment at airports are reviewed and summarized. Since one of the core concerns for PV and airport symbiosis is solar panel reflectivity, and because this data is largely estimated, a controlled experiment is conducted to determine worst-case values of front panel surface reflectivity and compare them to theoretical calculations. Then a general approach to implement solar PV systems in an airport is outlined and this approach is applied to a case study airport. The available land was found to be over 570 acres, which would generate more than 39,000% of the actual annual power demand of the existing airport. The results are discussed while considering the scaling potential of airport-based PV systems throughout the U.S.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

General Design Procedures for Airport-Based Solar Photovoltaic Systems

et al. 2017

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“…Some of these parameters are air-motor speed (ω), air pressure (pAir), and electrical energy generated by the generator (P) on the loading. By knowing these characteristics, it will be easier to operate the system, such as knowing how much pressure is required and the speed to be achieved to achieve specific power or to achieve the maximum power transfer [23][24][25]. To be able to know the characteristics of the SS-CAES system, it can be done by entering the variable value of speed and pressure on the mathematical equations from the system that has been created.…”

Section: Introductionmentioning

confidence: 99%

Power curves prediction using empirical data regression on small scale compressed air energy storage

Widjonarko

Soenoko

Wahyudi

et al. 2019

JMES

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The key to optimizing the system is to know the operating point of the system at the time of loading, or it is known as the power curve. However, to identify the power curve, the existing method is to model the mathematical of the system. Therefore some component characteristics need to be known and need additional observations if the component variable is unknown, and it becomes a long identification process. So, in this exploratory research will be presented the way to find out the power curve of a system without modeling mathematical of the system, but by using the polynomial regression technique. This regression technique form is using the empirical data of the power curve form parameter on SS-CAES prototype. The method is based on five approach model in which is the variation of loading sampling data to be used with the purpose is to find the best sampling of prediction. The data will be analyzed in the form of statistical parameters and the graph to show the evaluation process of this technique. From the results of the regression can be concluded that the power curve of SS-CAES can be identified with a high correlation value of 0.997 (99,745% accuracy) and the best way to take samples of data to be used in this technique is presented in the paper.

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“…Herein we review some of them: Kaldellis and Kokala [5] investigated an experimental analysis was conducted in the laboratory soft energy application and environmental protection (SELAB) to determine the effect of pollution on the energy performance of PV-panels quantitatively. Majid et al [6] showed that the efficiency of PV cell decrease 0.485% per 1°C, after the surface temperature increase than 25°C. Elhab B. R. et al [7] presented a mathematical approach to determine optimum tilt angles for solar collector.…”

Section: Introductionmentioning

confidence: 99%

The Impact of the Environmental Condition on the Performance of the Photovoltaic Cell

Abbas¹

2016

AJEE

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Abstract:The present study investigated the impact of weather conditions on the production performance of the photovoltaic (PV) module. The experiments have been conducted by using two identical PV module of 75 Watt each and they were placed in the same weather conditions in the summer season in Kirkuk city-Iraq. One of them was used as a conventional module as a reference panel and the other unit which has been used in all required tests. Water circulation has been used for cooling of the PV module to and very fine soil used to estimate the effect of each of hot weather and dust deposition on the performance of PV respectively. The results show that the fill factor (FF) and PV efficiency affected inversely with increasing in temperature, on the other hand cooling process contributed to increase the voltage generation across PV panel by 11.8%, while the reduction in voltage generation by unclean panel due to natural pollution deposition on the front of the panel for a period of three months was about 3.8% compared with clean panel and 13.8% if it has been compared with voltage production by panel when it has been cooled by water.

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Study on Performance of 80 Watt Floating Photovoltaic Panel

Cited by 74 publications

References 9 publications

General Design Procedures for Airport-Based Solar Photovoltaic Systems

General Design Procedures for Airport-Based Solar Photovoltaic Systems

Power curves prediction using empirical data regression on small scale compressed air energy storage

The Impact of the Environmental Condition on the Performance of the Photovoltaic Cell

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